[1]余志同,傅文渊.线性离散时不变系统的分数阶相位校正迭代学习控制[J].华侨大学学报(自然科学版),2022,43(4):518-525.[doi:10.11830/ISSN.1000-5013.202103008]
　YU Zhitong,FU Wenyuan.Fractional-Order Phase Correction Iterative Learning Control of Linear Discrete Time-Invariant Systems[J].Journal of Huaqiao University(Natural Science),2022,43(4):518-525.[doi:10.11830/ISSN.1000-5013.202103008]
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线性离散时不变系统的分数阶相位校正迭代学习控制()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第43卷
期数:
2022年第4期
页码:
518-525
栏目:
出版日期:
2022-07-18

文章信息/Info

Title:
Fractional-Order Phase Correction Iterative Learning Control of Linear Discrete Time-Invariant Systems
文章编号:
1000-5013(2022)04-0518-08
作者:
余志同1; 2; 3;  傅文渊1; 2; 3
1. 华侨大学 信息科学与工程学院, 福建 厦门 361021;2. 华侨大学 厦门市专用集成电路系统重点实验室, 福建 厦门 361008;3. 华侨大学 福建省电机控制与系统优化调度工程技术研究中心, 福建 厦门 361021
Author(s):
YU Zhitong1; 2; 3;  FU Wenyuan1; 2; 3
1. College of Information Science and Engineering, Huaqiao Univesity, Xiamen 361021, China; 2. Xiamen City Key Laboratory of Application Specific Iintegrated Circuit System, Xiamen 361008, China; 3. Fujian Province Engineering Technology Research Center of Motor Control and System Optimal Schedule, Huaqiao Univesity, Xiamen 361021, China
关键词:
分数阶;  相位校正;  迭代学习控制;  收敛精度
Keywords:
fractional-order;  phase correction;  iterative learning control;  convergence precision
分类号:
TP273
DOI:
10.11830/ISSN.1000-5013.202103008
文献标志码:
A
摘要:
针对带有随机干扰的线性离散时不变系统,提出一种分数阶相位校正迭代学习控制算法.设计一种新型相位超前校正与分数阶迭代学习控制相结合的迭代学习控制(ILC)学习律.基于频域分析方法,得到分数阶相位校正迭代学习控制在算法开、闭环两种情况下的频域收敛条件.结果表明:文中算法显著提高了ILC跟踪误差的收敛速度和收敛精度,具有先进性和有效性.
Abstract:
A fractional-order phase correction iterative learning control algorithm is proposed aiming at linear discrete time-invariant systems with random disturbances. A new iterative learning control(ILC)learning law combining phase advance correction and fractional-order iterative learning control is designed. Base on the frequency domain analysis method, the frequency domain convergence conditions of the fractional-order phase correction iterative learning control algorithm in both open and closed loops are obtained.The results show that the proposed algorithm can significantly improve the convergence speed and convergence precision of ILC tracking errors, and it is advanced and effective.

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备注/Memo

备注/Memo:
收稿日期: 2021-03-04
通信作者: 傅文渊(1983-),男,讲师,博士,主要从事智能信号处理及智能学习控制的研究.E-mail:fwy@hqu.edu.cn.
基金项目: 国家自然科学基金资助项目(61203369); 福建省中青年教育科研基金资助项目(JA15037)
更新日期/Last Update: 2022-07-20